International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences
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Design and Implement Search Engine Optimization Prediction System using Machine Learning

Authors: Jui More, Vaishnavi Gaikwad, Jyoti Lahange, Sayli Shinde, J.Y. Kapadnis

Country: India

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Abstract: Site improvement (web optimization) alludes to streamlining individual sites and pages to accomplish higher page positions in query items. Sites are generally streamlined for backlinks be that as it may, individual site pages are streamlined for explicit catchphrases. This paper proposes a structure in light of a bunch of rules for watchword examination and backlink age. The proposed structure depends on dataset prepared which recommends that page content ought to be watchword based and webpage traffic ought to be observed by referrals. Achieve better query items assuming your site content and title contain significant and applicable catchphrases and have the right amount of backlinks to assist with checking your site traffic You can rank your site to for The system additionally stresses that engineers and fashioners ought to consider legitimate watchword choice and external link establishment while dealing with programming advancement projects.

Keywords: Search Engine Optimization, Machine Learning, SVM


Paper Id: 230165

Published On: 2023-05-23

Published In: Volume 11, Issue 3, May-June 2023

Cite This: Design and Implement Search Engine Optimization Prediction System using Machine Learning - Jui More, Vaishnavi Gaikwad, Jyoti Lahange, Sayli Shinde, J.Y. Kapadnis - IJIRMPS Volume 11, Issue 3, May-June 2023.

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